Yearly Traffic Safety Analysis

405 CRASHES IN
IOWA, IA
2015

In 2015, Iowa County recorded 405 traffic crashes, which resulted in 5 fatalities and 154 injuries. A significant portion of these incidents were linked to environmental factors rather than driver error alone. The most notable statistical finding is the prevalence of animal-related collisions, which were cited as the primary contributing factor in 145 crashes, representing over a third of all incidents in the county.

405

Total Crash Events

5

Persons Killed

154

Persons Injured

5

Fatal Crash Events

Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (5) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Aggregate counts from crash, person, and vehicle records

Vulnerable Road User Casualties

Of the individuals killed or injured, the vast majority were motorists. A total of 5 motorists were killed and 150 were injured in crashes during this period. There were no pedestrian fatalities or injuries reported. Three cyclists were injured in collisions, but none were killed.

0

Cyclists Killed

5

Motorists Killed

0

Other Killed

3

Cyclists Injured

150

Motorists Injured

1

Other Injured

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crash patterns in Iowa County show a slight peak on weekends, with Saturday recording the highest number of incidents at 63. The single most frequent hour for crashes was 6 a.m., with 32 incidents, suggesting a morning commute risk. While a majority of crashes occurred during daylight (167 incidents), a substantial number also happened in dark conditions, with 78 on unlighted roadways and 11 on lighted ones.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The vast majority of crashes, 313 out of 405 (77.3%), resulted in no injuries. Incidents involving injuries totaled 87, with these being categorized as serious (10), minor (34), or possible (43). A total of 5 crashes were fatal, accounting for 1.2% of all incidents and resulting in 5 fatalities.

Outcome by Severity (Crash Events)

Fatal5fatal crashes1.2%
Serious Injury10serious injury crashes2.5%
Minor Injury34minor injury crashes8.4%
Possible Injury43possible injury crashes10.6%
No Injury313no injury crashes77.3%

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor to crashes was overwhelmingly identified as 'Animal,' accounting for 145 incidents or 35.8% of the total. Following this, driver-related actions such as 'Lost Control' (44 crashes, 10.9%) and 'Ran off road - straight' (39 crashes, 9.6%) were the next most common factors cited in crash reports.

Officer-Reported Primary Contributing Cause

Animal145 (35.8%)
Lost Control44 (10.9%)
Ran off road - straight39 (9.6%)
Driving too fast for conditions27 (6.7%)
Followed too close15 (3.7%)
Ran off road - left15 (3.7%)
FTYROW: From stop sign15 (3.7%)
Ran Stop Sign9 (2.2%)
Other (explain in narrative): Other8 (2%)
Improper or erratic lane changing7 (1.7%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

A substantial number of crashes occurred in seemingly ideal driving conditions. Reports indicate 177 crashes (43.7%) happened on dry roads, 143 (35.3%) in clear weather, and 167 (41.2%) during daylight hours. However, adverse conditions were also a factor, with 27 crashes on icy or frosty roads and 23 occurring during snowfall.

Weather

Clear143 (52.8%)
Cloudy63 (23.2%)
Snow23 (8.5%)
Rain21 (7.7%)
Freezing rain/drizzle7 (2.6%)
Blowing Snow6 (2.2%)
Fog, smoke, smog5 (1.8%)
Severe Winds2 (0.7%)
Sleet, hail1 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Weather condition at time of crash

Lighting

Daylight167 (61.2%)
Dark - roadway not lighted78 (28.6%)
Dark - roadway lighted11 (4.0%)
Dawn9 (3.3%)
Dusk7 (2.6%)
Dark - unknown roadway lighting1 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Lighting condition field

Road Surface

Dry177 (65.1%)
Ice/frost27 (9.9%)
Wet26 (9.6%)
Snow22 (8.1%)
Gravel14 (5.1%)
Slush3 (1.1%)
Mud, dirt1 (0.4%)
Sand1 (0.4%)
Water (standing or moving)1 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Road surface condition field

Vehicles & Demographics

Among the 715 people involved in crashes, the most represented age groups were 26-34 years old (134 individuals) and 45-54 years old (124 individuals). An analysis of the 553 vehicles involved shows that Ford was the most frequent make, with 110 vehicles. Chevrolet (including 'CHEV' variants) was second with 105 vehicles, followed by Dodge (including 'DODG' variants) with 41 vehicles.

Top Vehicle Makes (553 vehicles)

1
FORD110 (19.9%)
2
CHEVROLET63 (11.4%)
3
CHEV42 (7.6%)
4
DODGE27 (4.9%)
5
FREIGHTLINER17 (3.1%)
6
BUICK16 (2.9%)
7
CHRYSLER15 (2.7%)
8
VOLVO15 (2.7%)
9
GMC15 (2.7%)
10
TOYOTA14 (2.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

29 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (492 persons with recorded sex)

Male309 (62.8%)
Female183 (37.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events

Major Cause

The most frequently cited major cause for crashes was 'Animal,' which was attributed to 145 incidents. Driver actions followed, with 'Lost Control' being a factor in 44 crashes and 'Ran off road - straight' in 39 crashes. 'Driving too fast for conditions' was also a notable cause, contributing to 27 incidents.

Major Cause

1
Animal145 (36.6%)
2
Lost Control44 (11.1%)
3
Ran off road - straight39 (9.8%)
4
Driving too fast for conditions27 (6.8%)
5
Followed too close15 (3.8%)
6
Ran off road - left15 (3.8%)
7
FTYROW: From stop sign15 (3.8%)
8
Ran Stop Sign9 (2.3%)
9
Other (explain in narrative): Other8 (2%)

Showing top 9 of 41 reported. 32 additional (79 total) not shown: Improper or erratic lane changing, Swerving/Evasive Action, FTYROW: At uncontrolled intersection, Other (explain in narrative): No improper action, FTYROW: Making left turn, FTYROW: From driveway, Failed to keep in proper lane, Driver Distraction: Reaching for object(s)/fallen object(s), Driver Distraction: Inattentive/lost in thought, FTYROW: Other (explain in narrative), Operating vehicle in an reckless, erratic, careless, negligent manner, Driver Distraction: Other interior distraction, Made improper turn, Driver Distraction: Talking on a hand-held device, Driver Distraction: Manual operation of an electronic communication device, Driver Distraction: Exterior distraction, Driver Distraction: Adjusting devices (radio, climate), Ran Traffic Signal, FTYROW: From parked position, Equipment failure, Other (explain in narrative): Improper operation, Driver Distraction: Other electronic device activity, Crossed centerline (undivided), Passing: Other passing (explain in narrative), Passing: With insufficient distance/inadequate visibility, Failed to yield to emergency vehicle, Ran off road - right, Cargo/equipment loss or shift, FTYROW: To pedestrian, Improper Backing, Driver Distraction: Passenger, FTYROW: From yield sign.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

First Harmful Event

The initial event in a majority of crashes involved a collision with an animal, which occurred in 145 incidents. The second most common first harmful event was a collision with another vehicle in traffic, accounting for 110 crashes. Collisions with fixed objects were also significant, led by impacts with cable barriers (39 crashes) and ditches (28 crashes).

First Harmful Event

1
Collision with: Animal145 (35.9%)
2
Collision with: Vehicle in traffic110 (27.2%)
3
Collision with fixed object: Cable barrier39 (9.7%)
4
Collision with fixed object: Ditch28 (6.9%)
5
Non-collision events: Overturn/rollover23 (5.7%)
6
Collision with: Parked motor vehicle9 (2.2%)
7
Non-collision events: Jackknife5 (1.2%)
8
Collision with fixed object: Utility pole/light support5 (1.2%)
9
Other (explain in narrative)4 (1%)

Showing top 9 of 27 reported. 18 additional (36 total) not shown: Collision with fixed object: Other post/pole/support (explain in narrative), Collision with fixed object: Culvert/pipe opening, Non-collision events: Other non-collision (explain in narrative), Collision with fixed object: Fence, Collision with fixed object: Other fixed object (explain in narrative), Collision with fixed object: Guardrail - face, Collision with: Non-motorist (see non-motorist section - NOT a unit), Collision with: Struck/struck by object/cargo/person from other vehicle, Collision with: Thrown or falling object, Miscellaneous events: Hit and run, Non-collision events: Non-contact vehicle (phantom), Non-collision events: Vehicle went airborne, Collision with fixed object: Building, Collision with: Re-entering roadway, Collision with: Other non-fixed object (explain in narrative), Collision with fixed object: Ground, Collision with fixed object: Traffic sign support, Collision with fixed object: Embankment.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Roadway Junction / Feature

The majority of crashes, 190 incidents, occurred at non-junction locations along a roadway. Intersections were the site of a smaller but significant number of crashes, with four-way intersections accounting for 31 incidents and T-intersections for 15. Crashes related to driveway access were noted in 15 incidents.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature190 (69.3%)
2
Intersection: Four-way intersection31 (11.3%)
3
Intersection: T-intersection15 (5.5%)
4
Non-intersection: Driveway access (related, not in)11 (4%)
5
Intersection: Intersection with ramp4 (1.5%)
6
Non-intersection: Driveway access (within)4 (1.5%)
7
Interchange-related: Mainline, between ramps4 (1.5%)
8
Interchange-related: Off-ramp4 (1.5%)
9
Intersection: Y-intersection3 (1.1%)

Showing top 9 of 16 reported. 7 additional (8 total) not shown: Non-intersection: Other non-intersection (explain in narrative), Non-intersection: Bike lanes, Intersection: L-intersection, Intersection: Other intersection (explain in narrative), Interchange-related: On-ramp, Interchange-related: Off-ramp, diverge area, Non-intersection: Railroad grade crossing.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Vehicle Type

Passenger cars were the most common vehicle type involved in crashes, with 234 units recorded. Sport utility vehicles (105 units) and four-tire light trucks or pickups (88 units) were the next most frequent. Notably, 49 incidents involved a tractor/semi-trailer, highlighting a significant presence of commercial trucks in area collisions.

Vehicle Type

"Other" combines 9 smaller categories (21 records): Truck/trailer (5), Motorcycle (4), Cargo/panel van (3), Tractor/doubles (3), Motor home/recreational vehicle (2), Other light truck (<=10000 lbs) (1), Other bus (seats > 15) (1), Truck tractor (bobtail) (1), Small school bus (seats 9-15) (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Traffic Control Device

A large majority of crashes, 356 incidents, occurred on roadway segments where no traffic controls were present. In locations with traffic controls, stop signs were the most common device, present at the scene of 41 crashes. Traffic signals were a factor in 7 crashes.

Traffic Control Device

"Other" combines 3 smaller categories (3 records): Flashing traffic control signal (1), Warning sign (1), Work zone sign (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Most Damaged Area

Analysis of vehicle damage indicates that frontal impacts were the most common. The primary point of impact was the front for 107 vehicles, the front-driver side corner for 45 vehicles, and the front-passenger side corner for 43 vehicles. Rear impacts were noted on 33 vehicles, suggesting a smaller but notable share of rear-end type collisions.

Most Damaged Area

"Other" combines 10 smaller categories (109 records): Passenger side - rear (18), Top (17), Driver side - rear (17), Passenger side - middle (12), Rear - driver side corner (12), Other (explain in narrative) (11), Undercarriage (9), Rear - passenger side corner (8), Non-collision/no damage (4), Cargo loss (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Crashes by City

Within Iowa County, the highest volume of crashes was reported in Williamsburg, with 37 incidents. Marengo recorded the second-highest number with 24 crashes. Other municipalities with reported crashes include Victor (6), North English (3), and Parnell (1).

Crashes by City

1
WILLIAMSBURG37 (52.1%)
2
MARENGO24 (33.8%)
3
VICTOR6 (8.5%)
4
NORTH ENGLISH3 (4.2%)
5
PARNELL1 (1.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Paved vs Unpaved Road

Crashes occurred predominantly on paved roadways, with 374 incidents. However, a notable number of crashes, 29 in total, were reported on unpaved surfaces like gravel or dirt roads. This represents approximately 7.2% of crashes where the road surface type was specified.

Paved vs Unpaved Road

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Roadway Contributing Factor

Among roadway-related contributing factors, adverse surface conditions such as wet or icy pavement were the most commonly cited, contributing to 54 crashes. Other factors were noted far less frequently, with traffic backups from prior crashes being a factor in 7 incidents and ruts or holes in the road surface contributing to 3 incidents.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)54 (78.3%)
2
Traffic backup, prior crash7 (10.1%)
3
Ruts/holes/bumps3 (4.3%)
4
Work Zone (roadway-related)2 (2.9%)
5
Obstruction in roadway1 (1.4%)
6
Debris1 (1.4%)
7
Traffic backup, prior non-recurring incident1 (1.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Driver Condition

In cases where a driver's condition was noted as something other than 'apparently normal,' the most common factor was being asleep or fatigued, which was recorded for 19 drivers. Driving under the influence of alcohol was the next most frequent condition, cited for 9 drivers. Medical conditions and illness were also noted in a small number of cases.

Driver Condition

1
Asleep/fatigued19 (54.3%)
2
Under the influence of alcohol9 (25.7%)
3
Medical condition (seizure, reaction)4 (11.4%)
4
Illness/fainted2 (5.7%)
5
Visually impaired1 (2.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Property Damage

The most common estimated cost of property damage fell within the $1,500 to $7,500 range, which applied to 289 of the 405 crashes. High-damage incidents, with costs estimated at $25,000 or more, accounted for 17 crashes, or approximately 4.2% of the total. Crashes with damage estimated between $7,500 and $25,000 numbered 93.

Property Damage

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Manner of Collision

Single-vehicle, non-collision events were the dominant manner of collision, accounting for 219 crashes or 54.1% of all incidents. Among multi-vehicle crashes, rear-end collisions were the most frequent type, with 45 incidents (11.1%), followed by broadside collisions with 34 incidents (8.4%).

Manner of Collision

"Other" combines 3 smaller categories (10 records): Rear to side (5), Angle, oncoming left turn (4), Rear to rear (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Pre-Crash Driver Action

The most common action of vehicles immediately prior to a crash was moving straight ahead, which was the case for 326 vehicles involved. The next most frequent pre-crash actions were slowing or stopping (36 vehicles) and turning left (24 vehicles).

Pre-Crash Driver Action

1
Movement essentially straight326 (70.4%)
2
Slowing/stopping (deceleration)36 (7.8%)
3
Turning left24 (5.2%)
4
Turning right14 (3%)
5
Changing lanes14 (3%)
6
Legally Parked11 (2.4%)
7
Other (explain in narrative)8 (1.7%)
8
Backing6 (1.3%)
9
Stopped in traffic5 (1.1%)

Showing top 9 of 16 reported. 7 additional (19 total) not shown: Overtaking/passing, Negotiating a curve, Starting in road, Leaving a parked position, Illegally Parked/Unattended, Entering a parked position, Making U-turn.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Person Type

Of the 715 individuals involved in crashes, the vast majority were drivers, accounting for 644 people. Passengers comprised the next largest group with 67 individuals. A small number of non-motorists were also involved, including 3 bicyclists and 1 other non-motorist.

Person Type

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Person Injury Severity

Among the 715 people involved in traffic incidents, 5 sustained fatal injuries and 154 sustained non-fatal injuries. The injuries were categorized as serious for 21 individuals, minor for 62, and possible for 71. The majority of people involved were not physically injured.

Person Injury Severity

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Occupant Safety Equipment

Based on the limited data available for safety equipment usage, 104 individuals were recorded as using a shoulder and lap belt. Nine individuals were explicitly noted as not using any safety equipment. The use of child safety seats was recorded for 5 children.

Occupant Safety Equipment

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events

Vehicles Per Crash

Single-vehicle crashes were the most common type of incident, accounting for 276 of the 405 total crashes (68.1%). Two-vehicle collisions were the next most frequent, with 116 incidents (28.6%). Crashes involving three or more vehicles were rare, with only 13 such events recorded.

Vehicles Per Crash

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Iowa Crash Data, accessed programmatically via the ArcGIS Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.

Data Retrieval

  • Access method: ArcGIS Open Data API (SoQL queries)
  • Data format: Structured JSON via REST API
  • Record types queried: Crash events, person records, and vehicle unit records
  • Date filter applied: 2015-01-01 through 2015-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2015-01-01 through 2015-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 405
  • Total persons involved: 715
  • Total vehicles involved: 553

Analytical Methodology

  • Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
  • Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
  • Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
  • Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
  • Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
  • Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
  • AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.

Limitations & Disclaimers

  • Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
  • Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
  • Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
  • AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
  • Percentages are calculated from reported data and are subject to rounding.

Non-Affiliation Disclosure

This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.

Data License

The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.

Corrections & Feedback

If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.

Suggested Citation

ThatCarHitMe.com (Injuria.ai). "iowa, IA Crash Intelligence Report: 2015." Published September 9, 2026. Reporting period: 2015-01-01 to 2015-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2015-annual-report

About the Publisher

ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.

Questions about this report's data or methodology: data@injuria.ai

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